Saved in:
Bibliographic Details
Main Authors: Takahashi, Tomoya, Tu, Wei-Lin, Chen, Ji-Yao, Nomura, Yusuke
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2601.09326
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866915729518886912
author Takahashi, Tomoya
Tu, Wei-Lin
Chen, Ji-Yao
Nomura, Yusuke
author_facet Takahashi, Tomoya
Tu, Wei-Lin
Chen, Ji-Yao
Nomura, Yusuke
contents Studying finite-temperature properties with tensor networks is notoriously difficult, especially at low temperatures, due to the rapid growth of entanglement and the complexity of thermal states. Existing methods like purification and minimally entangled typical thermal states offer partial solutions but struggle with scalability and accuracy in low-temperature regime. To overcome these limitations, we propose a new approach based on generating-function matrix product states (GFMPS). By directly computing a large set of Bloch-type excited states, we construct Gibbs states that moderate the area-law constraint, enabling accurate and efficient approximation of low-temperature thermal behavior. Our benchmark results show magnificent agreement with both exact diagonalization and experimental observations, validating the accuracy of our approach. This method offers a promising new direction for overcoming the longstanding challenges of studying low-temperature properties within the tensor network framework. We also expect that our method will facilitate the numerical simulation of quantum materials in comparison with experimental observations.
format Preprint
id arxiv_https___arxiv_org_abs_2601_09326
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Probing the Dynamical Structure Factor of Quantum Spin Chains via Low-Temperature Gibbs States with Matrix Product State Subspace Expansion
Takahashi, Tomoya
Tu, Wei-Lin
Chen, Ji-Yao
Nomura, Yusuke
Strongly Correlated Electrons
Studying finite-temperature properties with tensor networks is notoriously difficult, especially at low temperatures, due to the rapid growth of entanglement and the complexity of thermal states. Existing methods like purification and minimally entangled typical thermal states offer partial solutions but struggle with scalability and accuracy in low-temperature regime. To overcome these limitations, we propose a new approach based on generating-function matrix product states (GFMPS). By directly computing a large set of Bloch-type excited states, we construct Gibbs states that moderate the area-law constraint, enabling accurate and efficient approximation of low-temperature thermal behavior. Our benchmark results show magnificent agreement with both exact diagonalization and experimental observations, validating the accuracy of our approach. This method offers a promising new direction for overcoming the longstanding challenges of studying low-temperature properties within the tensor network framework. We also expect that our method will facilitate the numerical simulation of quantum materials in comparison with experimental observations.
title Probing the Dynamical Structure Factor of Quantum Spin Chains via Low-Temperature Gibbs States with Matrix Product State Subspace Expansion
topic Strongly Correlated Electrons
url https://arxiv.org/abs/2601.09326